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Improving downtown in a mid-sized legacy city

Examining responses to potential downtown improvements in Flint, Michigan

Bibliographic Data

ID12811096
AuthorsVictoria Morckel (0000-0002-0591-3998, University of Michigan–Flint, corresponding author), Greg Rybarczyk (0000-0002-3920-2780, University of Michigan–Flint)
Year2015
Volume46
Issue4
Pages341-360
Publication date2015-07-09
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueCommunity Development (JOURNAL)
Journal identifiersISSN: 1557-5330 • E-ISSN: 1944-7485
PublisherRoutledge (PUBLISHER • GB)
DOI10.1080/15575330.2015.1061679
OpenAlexW1480950979
LanguageEN
Citations received4
References cited40

While many researchers have examined strategies for revitalizing downtowns, few have done so in small or mid-sized legacy cities. This article adds to the literature by examining 1263 survey responses to statements about potential improvements to the downtown area of Flint, Michigan (USA). Descriptive statistics were used to identify perceptions of the most promising strategies for improvement. Those strategies were further analyzed using regression methods, to determine which characteristics of participants influenced responses. We found that while there are many improvements that might encourage people to come downtown – such as reducing crime, having more to do, making parking easier, and having suitable housing – some traditional improvements advocated by planners (involving proximity, walkability, and bikeability) were not desired. Additionally, we found that responses appeared to be influenced by age, residency status, and perception of downtown, but not by education level, frequency of visiting, or whether or not one currently works downtown

Archaeology · Built environment · Civil engineering · Descriptive statistics · Downtown · Geography · Perception · Walkability · Engineering · Place Attachment and Urban Studies · Psychology · Urban Green Space and Health · Urban Transport and Accessibility

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Unique citing works4
Citations per year0.57
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 4

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